Mca-SEVNLDAEFK(Dnp)-NH2 integrates a fluorescent donor and quencher pair within a protease-sensitive peptide. Residue arrangement supports kinetic studies of cleavage events. Researchers track fluorescence restoration to measure catalytic rates. Uses include enzyme profiling, mechanistic evaluation, and substrate design.
CAT No: R2541
CAS No:1802078-32-5
Synonyms/Alias:1802078-32-5;Mca-SEVNLDAEFK(Dnp)-NH2;Mca-(Asn670,Leu671)-Amyloid b/A4 Protein Precursor770 (667-675)-Lys(Dnp) amide Ammonium;Mca-(Asn670,Leu671)-Amyloid beta/A4 Protein Precursor770 (667-675)-Lys(Dnp) amide ammonium salt;Unk-Ser-Glu-Val-Asn-Leu-Asp-Ala-Glu-Phe-Lys(Dnp)-NH2;HY-P4920;FM110963;CS-0674983;
Mca-SEVNLDAEFK(Dnp)-NH2 is a synthetic peptide substrate engineered for advanced biochemical and enzymatic studies, particularly in the context of protease activity assays. Featuring a sequence derived from natural protein substrates, this peptide incorporates a 7-methoxycoumarin-4-acetyl (Mca) fluorophore at the N-terminus and a dinitrophenyl (Dnp) quencher at the lysine side chain, enabling sensitive fluorescence-based detection of peptide cleavage events. Its design allows for precise monitoring of proteolytic processes, making it a valuable tool in research focused on enzyme kinetics, substrate specificity, and inhibitor screening. The sequence and labeling strategy support its utility in a wide range of in vitro experimental systems where real-time, quantitative analysis of protease function is required.
Protease activity assays: Mca-SEVNLDAEFK(Dnp)-NH2 is widely utilized as a fluorogenic substrate in the quantification of protease activity, especially for enzymes such as caspases and other cysteine proteases. Upon enzymatic cleavage at the designated peptide bond, the spatial separation of the Mca fluorophore from the Dnp quencher results in a measurable increase in fluorescence, providing a direct and sensitive readout of proteolytic activity. This property enables researchers to perform kinetic analyses, compare enzyme efficiencies, and evaluate the effects of experimental variables on protease function with high temporal resolution.
Enzyme inhibitor screening: The peptide's dual-label design makes it exceptionally suitable for high-throughput screening of protease inhibitors. By monitoring changes in fluorescence in the presence of candidate compounds, scientists can rapidly assess the potency and specificity of small molecule or peptide-based inhibitors. This application is critical in early-stage drug discovery workflows, where the identification of effective modulators of protease activity underpins the development of new research tools and potential therapeutic leads.
Substrate specificity profiling: The defined amino acid sequence of Mca-SEVNLDAEFK(Dnp)-NH2 allows for detailed investigation of protease substrate preferences. By systematically modifying the peptide sequence or testing it alongside related substrates, researchers can elucidate the structural determinants that govern enzyme-substrate recognition. This approach provides insights into protease selectivity, informs the rational design of optimized substrates, and supports studies aimed at mapping the substrate repertoire of target enzymes.
Biochemical pathway elucidation: In cell-free systems or complex biochemical mixtures, the peptide serves as a probe to track the activity of specific proteases implicated in regulated protein turnover, signaling cascades, or apoptotic processes. The ability to detect proteolytic events in real time facilitates the dissection of enzymatic pathways, enabling the identification of active protease species and their functional roles within multi-component biological systems. Such studies contribute to a deeper understanding of proteolytic regulation in physiological and pathological contexts.
Analytical method development: Mca-SEVNLDAEFK(Dnp)-NH2 supports the refinement of fluorescence-based analytical techniques for protease detection and quantification. Its robust signal-to-noise characteristics and reproducible cleavage kinetics make it an ideal standard for validating assay platforms, calibrating detection instrumentation, and establishing baseline parameters for quantitative measurements. Researchers benefit from its consistent performance in both manual and automated assay formats, enhancing the reliability and comparability of experimental data across laboratories.
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